000923043 000__ 05071cam\a2200529Ii\4500
000923043 001__ 923043
000923043 005__ 20230306151004.0
000923043 006__ m\\\\\o\\d\\\\\\\\
000923043 007__ cr\cn\nnnunnun
000923043 008__ 191023s2020\\\\si\a\\\\o\\\\\000\0\eng\d
000923043 019__ $$a1125073356$$a1125268921$$a1126000311$$a1126613952$$a1136388043
000923043 020__ $$a9789813295858$$q(electronic book)
000923043 020__ $$a9813295856$$q(electronic book)
000923043 020__ $$z9789813295841
000923043 020__ $$z9813295848
000923043 0247_ $$a10.1007/978-981-32-9585-8$$2doi
000923043 0247_ $$a10.1007/978-981-32-9
000923043 035__ $$aSP(OCoLC)on1124839700
000923043 035__ $$aSP(OCoLC)1124839700$$z(OCoLC)1125073356$$z(OCoLC)1125268921$$z(OCoLC)1126000311$$z(OCoLC)1126613952$$z(OCoLC)1136388043
000923043 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dLQU$$dOCLCF$$dUKMGB$$dSFB
000923043 049__ $$aISEA
000923043 050_4 $$aTK5105.5
000923043 08204 $$a004.6$$223
000923043 24500 $$aComputational network application tools for performance management /$$cMillie Pant, Tarun K. Sharma, Sebastián Basterrech, Chitresh Banerjee, editors.
000923043 264_1 $$aSingapore :$$bSpringer,$$c2020.
000923043 300__ $$a1 online resource (xii, 267 pages) :$$billustrations.
000923043 336__ $$atext$$btxt$$2rdacontent
000923043 337__ $$acomputer$$bc$$2rdamedia
000923043 338__ $$aonline resource$$bcr$$2rdacarrier
000923043 4901_ $$aAsset analytics,$$x2522-5162
000923043 504__ $$aIncludes bibliographical references.
000923043 5050_ $$aPerformance Enhanced Hybrid Memetic Framework for Effective Coverage Based Test Case Optimization -- An Optimization Procedure for Quadratic Fractional Transportation Problem -- A Nature Inspired PID like Fuzzy Knowledge Based Fractional Order Controller for Optimization -- Neuro-Fuzzy-Rough Classification for Increasing Efficiency and Performance in Case-Based Reasoning Retrieval -- Better Performance of Human Action Recognition from Spatiotemporal Depth Information Features Classification -- Selecting Appropriate Multipath Routing In Wireless Sensor Networks for Improvisation of Systems Efficiency and Performance -- A Classification of ECG Arrhythmic Analysis Based on Performance Factors using Machine Learning Approach -- A Time Efficient Semi Automatic Active Contour Model of Liver Tumor Segmentation from CT Images -- Denoising 1d Signal Using Wavelets for Signal Quality Enhancement.
000923043 506__ $$aAccess limited to authorized users.
000923043 520__ $$aThis book explores a range of important theoretical and practical issues in the field of computational network application tools, while also presenting the latest advances and innovations using intelligent technology approaches. The main focus is on detecting and diagnosing complex application performance problems so that an optimal and expected level of system service can be attained and maintained. The book discusses challenging issues like enhancing system efficiency, performance, and assurance management, and blends the concept of system modeling and optimization techniques with soft computing, neural network, and sensor network approaches. In addition, it presents certain metrics and measurements that can be translated into business value. These metrics and measurements can also help to establish an empirical performance baseline for various applications, which can be used to identify changes in system performance. By presenting various intelligent technologies, the book provides readers with compact but insightful information on several broad and rapidly growing areas in the computation network application domain. The books twenty-two chapters examine and address current and future research topics in areas like neural networks, soft computing, nature-inspired computing, fuzzy logic and evolutionary computation, machine learning, smart security, and wireless networking, and cover a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book was written to serve a broad readership, including engineers, computer scientists, management professionals, and mathematicians interested in studying tools and techniques for computational intelligence and applications for performance analysis. Featuring theoretical concepts and best practices in computational network applications, it will also be helpful for researchers, graduate and undergraduate students with an interest in the fields o f soft computing, neural networks, machine learning, sensor networks, smart security, etc.
000923043 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 23, 2019).
000923043 650_0 $$aComputer networks$$xManagement.
000923043 650_0 $$aArtificial intelligence.
000923043 7001_ $$aPant, Millie,$$d1979-$$eeditor.
000923043 7001_ $$aSharma, Tarun K.$$eeditor.
000923043 7001_ $$aBasterrech, Sebastián,$$eeditor.
000923043 7001_ $$aBanerjee, Chitresh,$$eeditor.
000923043 77608 $$iPrint version: $$z9813295848$$z9789813295841$$w(OCoLC)1107563408
000923043 830_0 $$aAsset analytics.
000923043 852__ $$bebk
000923043 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-32-9585-8$$zOnline Access$$91397441.1
000923043 909CO $$ooai:library.usi.edu:923043$$pGLOBAL_SET
000923043 980__ $$aEBOOK
000923043 980__ $$aBIB
000923043 982__ $$aEbook
000923043 983__ $$aOnline
000923043 994__ $$a92$$bISE